Triple
T936329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAR |
E20202
|
entity |
| Predicate | notationFeature |
P6184
|
FINISHED |
| Object | uses letters to denote powered axles |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: uses letters to denote powered axles | Statement: [AAR, notationFeature, uses letters to denote powered axles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notationFeature Context triple: [AAR, notationFeature, uses letters to denote powered axles]
-
A.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
B.
notation
chosen
Indicates a conventional way of symbolically representing or writing something, such as concepts, quantities, or operations, within a specific system.
-
C.
notationPattern
Indicates a recurring way in which something is symbolically represented or written, such as a consistent style or structure of notation used for an entity or concept.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b36558588190a2a9c710073624d1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.